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Saturday, March 10, 2012

Population Growth in Prince
William County, Virginia and its Implications on the Environment.

ABSTRACT

This study will examine the continuous urban sprawl and
suburban development in Prince William County, Virginia. Prince William County is located in the
region of Northern Virginia, which is a part of the Washington DC Metropolitan
greater region. Urban development
disrupts hydrological and ecological systems, in addition to isolating and
degrading local natural habitats. Over
the past few decades, Prince William County has transformed from a rural area
with two main population centers, Manassas and Woodbridge, to a thriving
society. Today, these two population
centers now are interconnected with a steady stream of roads and
neighborhoods. 20 years ago, this area
was quiet and had quite a lower population. In 20 years, the population has
almost doubled from approximately 216,000 in 1990 to approximately 402,000 in
2010. In addition the county is projected to grow to approximately 555,000 in
another 20 years; the county had nearly doubled its population every 20 years
since 1950 (population was 22,000 in 1950).
The growth of this county has led to a decline in agriculture and an
increase in pollution. These constraints
from growth and development have ultimately resulted in several ecological
issues that this study will attempt to address. Furthermore, this study will identify the
spatial patterns associated with the growth and how it has grown over the
years.

RASTER LAYERS

Maps (i.e. Historic, topographic, pre-1990 census maps) – Any scanned map that has features that can
be digitized to fill in gaps from all other data used.

SRTM – Any type of elevation data needs to be used in order
to explain why certain areas have not been affected by urban sprawl.

Orthorectified Aerial Imagery – This type of imagery will
provide most of the historical data needed to determine foundation data for
comparing the present to the past. Each
image used can be digitized to extract data into vector format.

Satellite Imagery – This type of imagery will allow various
types of sensors to determine changes via comparing two or more images identify
change detection in vegetation, ecology, infrastructure, and other important
features in foundation data.

Table 1.
Satellite remote sensing data for ecological research.

Satellite

Launch

Sensors

spectrum

spatial resolution (m)

temporal resolution (days)

Landsat

1972

MSS, TM

V, IR

15-80

16

SPOT

1986

HRV

V, IR

10-20

5-26

IRS

1988

LISS, WiFS

V, IR

5-200

5-24

NOAA

1970

AVHRR

V, IR

1100

0.5

OrbView

1998

SeaWiFS

V, IR

1100

1

Terra

1999

MODIS

V, IR

250-1000

2

ERS

1991

AMI

microwave

20

variable

RADARSAT

1995

SAR

microwave

20

“

IKONOS

2000

IKONOS

V, IR

1-4

“

KOMPSAT

2000

EOC, OSMI

V

6-800

“

Source:http://www.klter.org/EVENTS/Conference00/html/leegusung.htm

VECTOR LAYERS

LULC (Land use land cover), including current and historical
datasets – This provides an idea of
where the different feature classes of land type and uses are located.

Census: 1990 and newer census tracts, population – Census
data reveals where the population is with any given area.

Hydrographic: rivers, streams, lakes, watershed – Hydrographic
features are part of a foundation dataset.

Infrastructure: roads, rails, powerlines, pipelines – Infrastructure
features are part of a foundation dataset.

Environment: Air Quality maintenance area, water quality
monitoring station – Reveals location of areas that monitor changes in the
environment. This allows for the
validity of data acquired in relation to air and water quality data compared to
sensors that capture quality via remote sensing.

Boundary: County and cities – Provides an outline for the
areas of interest.

METHODOLOGY

The methodology used for studying the issue of population
affecting the local ecology requires two different datasets themed to a
specific time frame, one pre-1990 dataset and one post-1990 dataset. The area of interest that will be studied is
within the county borders of Prince William County, Virginia, including the
cities of Occoquan, Manassas, and Manassas Park. A foundation dataset based on the
aforementioned criteria is needed to identify changes and challenges that urban
growth has had within the county. GIS
allows this foundation dataset to be overlaid with land cover and other raster
and vector files that have a relation to identifying the affects of increased
population in the county with files that can help determine factors that affect
the ecology such has changes in county infrastructure.

In order to accomplish this, GIS plays an instrumental role
in conducting spatial analysis between feature classes and identifying
relationships among the two topics: population and ecology.

Not all datasets are readily available in can be used
immediately for spatial analyses. Most
of all raster files in this project will have to be scanned and inputted into
the system. At this point, each file,
whther it is a photographic image or a map needs to be spatially referenced in
the area it is detailing. Digitizing
these types of files is a necessity once the files are geo-referenced in order
to extrapolate any valuable vector datasets from the map or images, such as
landcover and landuse, vegetation, missing pieces to infrastructure (i.e.
roads, buildings, parks, waterways, et cetera), et cetera. Most of the raster files that are not used
for creating vector datasets will be used for identifying air quality,
pollution, water quality, and most other ecological readings within the county.

Population data acquired from the U.S. Census Bureau and
Aerial Photography will be monitored over the past 60 years, in 5 to 10 year
increments depending on how much the population has changed the landscape of
the county. Each 10 year increment
changes will be identified in GIS and then compared to see the progression of
change temporally. The decrease of
agricultural land will also be identified in GIS via this process.

CONCLUSION

The results of this project should determine what areas
within Prince William County have endured more drastic changes than other
areas, as well as what areas need to be protected from any further
development. In addition, this project
will visually and temporally depict the changes over time in regards to population
growth, infrastructure changes, changes in water levels, air quality
animations, and vegetation changes.
Overall, the results will identify spatial patterns that have
directly impacted how the area has grown into what it is today from what it was
60 years ago, while simultaneously affecting the ecology of the area.

LIMITATIONS

This most anticipated roadblock will be the acquisition of
data needed to fulfill all the requirements in order to do spatial analysis and
observations. Secondary to do this, the
time involved to complete this project will be dependent on the amount of
change and extraction that is needed from the ingestion of maps or photographic
images. The more gaps in the vector
data, the more time needed to extract from the raster files.